Big plans for my 2nd semester

As the previous experience has shown, it’s hard to cover more than one course in one semester (this way of measuring my learning time seems most appropriate), if you have to work at the same time. Or rather one course and a half. Last semester, these were an introduction to statistics and a bit of R. Initially, I had huge plans for the upcoming semester. While learning statistics and earlier some Python basics I got a bit tired of constant guesswork and having to learn separate pieces of underlying fundamentals, without getting the whole picture. So I totally felt like taking two basic courses in this semester, namely some refresher in math and some intro to computer science.

As to computer science, I really liked the description of CS50, a Harvard CS course by David Malan, which has its online representation both as a static archive and as a MOOC at edX.org. The thing is that:

  • it lasts 10 weeks
  • it has 2 lectures every week, about an hour long each
  • it has 1 seminar a week, about an hour long
  • it includes 9 problem sets, estimated completion time 10 to 20 hours each
  • it includes 1 final project

Well, that’s definitely not what I’m likely to be able to cover before summer, especially if it is combined with a math course. Time for tough decisions. After some hesitation I decided that math comes first:

  • as a more basic subject
  • the thing I really needed while learning stats
  • more realistic to complete by the end of this semester.

There are actually two courses that seem quite appropriate for my needs (and I need to refresh some real basics):

I’m not sure about the latter, but Precalculus looks very promising in terms of at least answering some unresolved questions (simple, but very annoying) I already have after dealing with statistics.

So that’s what going to be my core subject for the semester, just like Statistics was last semester. Now, what about the remaining ‘half a course’ to complete my schedule? Well, I failed to complete Data Analysis last semester and I also want to have some revision of what I learnt about statistics last year. That’s what I think I’m going to be dealing with for the rest of my learning time. Stanford is offering a course in statistical learning (as far as I understand this stands for statistics combined with some machine learning approaches). I hope it won’t be as challenging as it could be after I have acquired some basic skills in handling R (and this course is based on R).

So these are my one and a half courses I’m going to take in this semester. As to CS, I do hope to take it in the summer.

A couple of links for those who also might need some school math refresher:

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It’s not easy being me

Just to complain a bit. But also probably somebody will be able to make more use of it than me.

By the end of summer I had a perfectly minimalistic learning plan for the autumn: R and Statistics. Isn’t it sweet? Just that and nothing else at least till December. Well, and a tiny bit of Python (Codecademy) at the background.

And here are some of the courses that turned up out of the blue right as soon as I started implementing my Perfect Plan.

  • Learning from Data at edX, began on September, 30
  • Social Network Analysis at Coursera, begins on October, 7
  • An iteration of Introduction to Interactive Programming in Python at Coursera. A course I failed to finish last spring because I got enrolled in School of Data Mission. Begins on October, 7
  • The Future of Storytelling at some Iversity (a new US MOOC platform, as far as I understand). Not sure it’s worth watching, but might be worth having a look at. Begins on October, 25 UPD. Has begun. No, definitely not worth wasting time on. I don’t mean the course is bad – I don’t know. But not what I think I need now.
  • Data Analysis at Coursera, begins on October, 28

Not to mention the upcoming (not sure when exactly, but this autumn) new iteration of School of Data MOOC (Data Explorer Mission).

Feel like Horrid Henry.

Horrid Henry

UPD. A new iteration of Python Mechanical MOOC is starting on October 21. Bingo!

Python: An Upcoming Mechanical MOOC

images

I’ve just had an astonishing experience. I was kind of looking for a pic for this post and I decided to be trivial and to simply use Python logo. It can’t be a problem to find it online, can it? Just type “python” in Google, switch to images and here you are. Oh wait. There are also snakes called pythons…

*Okay face*

I had totally forgotten about their existence.

I won’t post those pythons here, because I know some people are afraid of snakes and detest the way they look. Although I’d love to actually.

Now, what I was actually going to say is that a cool Python mechanical MOOC is just about to start. I’ve already subscribed. It’s beginning in June and, judging by the archive of its previous round, it lasts 8 weeks. What is special about this course, is that there are no instructors there whatsoever. But there are peers with whom you can discuss the learning problems, tasks and what not. And well, there’s also a great Q&A Forum at Codecademy. And many other forums and communities online.

By the way, the link to this MOOC was kindly sent to me by my awesome Data Expedition teammate. That’s what I call a p2p community.